Automatic Speech Recognition
Transformers
Safetensors
PyTorch
arkasr
text-generation
speech
audio
ark-asr
custom_code
Eval Results
Instructions to use AutoArk-AI/ARK-ASR-0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AutoArk-AI/ARK-ASR-0.6B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="AutoArk-AI/ARK-ASR-0.6B", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("AutoArk-AI/ARK-ASR-0.6B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| - dataset: | |
| id: hf-audio/open-asr-leaderboard | |
| task_id: mean_wer | |
| value: 6.03 | |
| date: '2026-06-03' | |
| source: | |
| url: /hf-audio | |
| name: open-asr-leaderboard | |
| user: hf-audio | |
| - dataset: | |
| id: hf-audio/open-asr-leaderboard | |
| task_id: rtfx | |
| value: 132.55 | |
| date: '2026-06-03' | |
| source: | |
| url: /hf-audio | |
| name: open-asr-leaderboard | |
| user: hf-audio | |
| - dataset: | |
| id: hf-audio/open-asr-leaderboard | |
| task_id: ami_wer | |
| value: 11.54 | |
| date: '2026-06-03' | |
| source: | |
| url: /hf-audio | |
| name: open-asr-leaderboard | |
| user: hf-audio | |
| - dataset: | |
| id: hf-audio/open-asr-leaderboard | |
| task_id: earnings22_wer | |
| value: 10.07 | |
| date: '2026-06-03' | |
| source: | |
| url: /hf-audio | |
| name: open-asr-leaderboard | |
| user: hf-audio | |
| - dataset: | |
| id: hf-audio/open-asr-leaderboard | |
| task_id: gigaspeech_wer | |
| value: 8.95 | |
| date: '2026-06-03' | |
| source: | |
| url: /hf-audio | |
| name: open-asr-leaderboard | |
| user: hf-audio | |
| - dataset: | |
| id: hf-audio/open-asr-leaderboard | |
| task_id: librispeech_clean_wer | |
| value: 1.87 | |
| date: '2026-06-03' | |
| source: | |
| url: /hf-audio | |
| name: open-asr-leaderboard | |
| user: hf-audio | |
| - dataset: | |
| id: hf-audio/open-asr-leaderboard | |
| task_id: librispeech_other_wer | |
| value: 3.89 | |
| date: '2026-06-03' | |
| source: | |
| url: /hf-audio | |
| name: open-asr-leaderboard | |
| user: hf-audio | |
| - dataset: | |
| id: hf-audio/open-asr-leaderboard | |
| task_id: spgispeech_wer | |
| value: 2.89 | |
| date: '2026-06-03' | |
| source: | |
| url: /hf-audio | |
| name: open-asr-leaderboard | |
| user: hf-audio | |
| - dataset: | |
| id: hf-audio/open-asr-leaderboard | |
| task_id: tedlium_wer | |
| value: 2.43 | |
| date: '2026-06-03' | |
| source: | |
| url: /hf-audio | |
| name: open-asr-leaderboard | |
| user: hf-audio | |
| - dataset: | |
| id: hf-audio/open-asr-leaderboard | |
| task_id: voxpopuli_wer | |
| value: 6.63 | |
| date: '2026-06-03' | |
| source: | |
| url: /hf-audio | |
| name: open-asr-leaderboard | |
| user: hf-audio | |